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Making Social Sciences More ScientificThe Need for Predictive Models$
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Rein Taagepera

Print publication date: 2008

Print ISBN-13: 9780199534661

Published to Oxford Scholarship Online: September 2008

DOI: 10.1093/acprof:oso/9780199534661.001.0001

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Forbidden Areas and Anchor Points

Forbidden Areas and Anchor Points

Chapter:
(p.95) 8 Forbidden Areas and Anchor Points
Source:
Making Social Sciences More Scientific
Author(s):

Rein Taagepera (Contributor Webpage)

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780199534661.003.0008

The outcomes of sociopolitical processes often depend on the factor in shortest supply; this makes multiplication of factors superior to their addition. Naïve linear regression may not detect all relationships between physical or social factors, because nonlinear relationships predominate. When x and y can conceptually take only positive values, the simplest conceptually acceptable fit is to connect y to x raised to a power (an exponent). This means that linear regression should be carried out on the logarithms of x and y, not on x and y. Various other constraints, such as forbidden areas and anchor points, lead to exponential, simple logistic, and more complex patterns.

Keywords:   anchor points, constraints, exponential patterns, forbidden areas, linear regression, logistic patterns, multiplication of factors, nonlinear relationships, regression on logarithms

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